This invention is in the field of pipeline inspection. In one of its aspects, the invention is directed to the evaluation of the worst case corrosion in a pipeline from sampled measurements.
Maintaining the integrity of pipelines is a fundamental function in maintaining the economic success and minimizing the environmental impact of modern oil and gas production fields and systems. In addition, pipeline integrity is also of concern in other applications, including factory piping systems, municipal water and sewer systems, and the like. Similar concerns exist in the context of other applications, such as production casing of oil and gas wells. As is well known in the field of pipeline maintenance, corrosion and ablation of pipeline material, from the fluids flowing through the pipeline, will reduce the thickness of pipeline walls over time. In order to prevent pipeline failure, it is of course important to monitor the extent to which pipeline wall thickness has been reduced, so that timely repairs or replacement can be made.
The direct physical measurement of pipeline wall thickness is not practical because of the necessarily destructive nature of such measurement. Accordingly, various indirect pipeline wall thickness measurement techniques have been developed over the years. The most widely used measurement technologies acquire measurements of thickness at selected locations along a producing pipeline, such locations either randomly selected or specifically selected based on models or other assumptions of the most vulnerable locations to loss of wall thickness. These measurement technologies include ultrasonic measurement, and imaging by way of x-rays or radiography (RT), each of which examine pipeline walls from the exterior at specific locations (e.g., over a one foot section). However, the exterior of the pipeline must be directly accessed to obtain measurements according to these technologies. In extreme environments, this exterior access can require removal and replacement of thermal insulation, for example. To the extent that portions of the pipelines are underground, RT and ultrasonic tomography (UT) measurements are either not done, or require excavation. As such, it is not practical to acquire RT and UT measurements at small intervals along the entire length of a pipeline. Rather, for these and other reasons, these measurement technologies are typically carried out by random or semi-random sampling of wall thickness along the pipeline.
In the context of pipeline integrity, the extreme value of minimum wall thickness (or, conversely, maximum wall thickness loss) is of concern. Because corrosion is the leading cause of wall thickness loss of pipelines, in practice, this minimum wall thickness value is often referred to as the “worst case corrosion”. Accordingly, sampled measurement approaches are useful only to the extent that the sample measurements lend insight into the extreme minimum value. Fundamental statistical theory can provide such insight, under the assumption that the population of wall thickness measurements along the entire length of the pipeline (e.g., a measurement taken in each one-foot section along the pipeline length) follows a known statistical distribution. In other words, assuming a statistical distribution of wall thicknesses along the length of the pipeline, a reasonable sample size of measurements can then provide an indication of the maximum wall thickness loss to a certain confidence level. Unfortunately, it has been observed that measurements of wall thickness along the length of an actual pipeline do not typically follow a well-behaved statistical distribution. Worse yet, it has been observed that wall thickness measurement distributions vary widely from pipeline to pipeline. As a result, it is difficult to characterize the extreme value of worst case corrosion along a pipeline from these sampled measurements of pipeline thickness, to any reasonable confidence level.
Another pipeline wall thickness measurement technology is referred to as “in-line inspection” (ILI). According to this technology, a vehicle commonly referred to as a “pig” travels in the interior of the pipeline along its length, propelled by the production fluid itself or otherwise towed through the pipeline. The pig includes transducers that indirectly measure the wall thickness of the pipeline repeatedly along the pipeline length as the pig travels. Measurement technologies used in ILI include magnetic flux leakage techniques that measure the extent to which a magnetic field can be induced into the pipeline wall, from which the wall thickness can be inferred. ILI inspection can also be carried out using ultrasonic energy, as well-known in the art. As such, ILI can acquire measurements of wall thickness at small intervals along the entire length of a pipeline. Unfortunately, ILI monitoring cannot be applied to all pipelines, because of factors such as construction, location, or geometry.
By way of further background, it is known to characterize pipeline integrity by applying sample thickness measurements to a predictive model of the pipeline. Known predictive models apply parameters such as properties of the fluid carried by the pipeline, pressure, temperature, flow rate, and the like, such that a minimum wall thickness can be calculated given sample measurements of the wall thickness. The accuracy of such computer simulations in characterizing the minimum wall thickness of course depends on the accuracy with which the model corresponds to the true behavior of the pipeline. And, in turn, the accuracy of the model depends on the accuracy of the assumptions underlying the model to the actual pipeline. But in practice, real-world pipelines vary widely from one another in corrosion behavior, due to structural and environmental variations that are not contemplated by the model or its underlying assumptions. As more complicated models are formulated to include the effects of these variations, the resulting computations will of course also become more complicated.
By way of further background, it is known to evaluate equipment reliability by selecting a statistical distribution, and applying Monte Carlo simulations to that statistical distribution, to plan a reliability evaluation.
By way of further background, our copending U.S. patent application Ser. No. 12/164,971, filed Jun. 30, 2008, entitled “Rapid Data-Based Adequacy Procedure for Pipeline Integrity Assessment”, fully incorporated herein by this reference, discloses a method and system for evaluating the sample coverage of ultrasonic or radiography (UT/RT) measurements of pipeline wall thickness for statistical validity. This approach uses a data library of distributions of in-line inspection (ILI) measurements for some pipelines, and generates statistics from random sample simulation of those distributions at various sample coverages. The sampled UT/RT measurements from another pipeline are used to identify one or more ILI-measured pipeline datasets to which it is most similar. The statistics from the simulations of those most similar pipeline datasets are then used to determine whether the sample coverage of the UT/RT measurements is sufficient to draw desired conclusions about the extreme value of wall loss in the sampled pipeline.